118 lines
3.3 KiB
Markdown
118 lines
3.3 KiB
Markdown
# PIQA
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## Overview
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PIQA (Physical Interaction QA) is a benchmark for evaluating AI models' understanding of physical commonsense - how objects interact in the physical world and what happens when we manipulate them.
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## Task Description
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- **Task Type**: Physical Commonsense Reasoning
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- **Input**: Goal/question with two possible solutions
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- **Output**: More physically plausible solution (A or B)
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- **Focus**: Physical world knowledge and intuitive physics
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## Key Features
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- Tests understanding of physical object properties
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- Binary choice between plausible/implausible solutions
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- Requires intuitive physics reasoning
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- Covers everyday physical scenarios
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- Adversarially filtered to reduce biases
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## Evaluation Notes
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- Default configuration uses **0-shot** evaluation
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- Uses simple multiple-choice prompting
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- Evaluates on validation split
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- Simple accuracy metric
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## Properties
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| Property | Value |
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|----------|-------|
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| **Benchmark Name** | `piqa` |
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| **Dataset ID** | [extraordinarylab/piqa](https://modelscope.cn/datasets/extraordinarylab/piqa/summary) |
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| **Paper** | N/A |
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| **Tags** | `Commonsense`, `MCQ`, `Reasoning` |
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| **Metrics** | `acc` |
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| **Default Shots** | 0-shot |
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| **Evaluation Split** | `validation` |
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| **Train Split** | `train` |
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## Data Statistics
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| Metric | Value |
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|--------|-------|
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| Total Samples | 1,838 |
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| Prompt Length (Mean) | 426.52 chars |
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| Prompt Length (Min/Max) | 220 / 2335 chars |
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## Sample Example
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**Subset**: `default`
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```json
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{
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"input": [
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{
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"id": "a0600392",
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"content": "Answer the following multiple choice question. The entire content of your response should be of the following format: 'ANSWER: [LETTER]' (without quotes) where [LETTER] is one of A,B.\n\nHow do I ready a guinea pig cage for it's new occupants?\n ... [TRUNCATED] ... ps, you will also need to supply it with a water bottle and a food dish.\nB) Provide the guinea pig with a cage full of a few inches of bedding made of ripped jeans material, you will also need to supply it with a water bottle and a food dish."
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}
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],
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"choices": [
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"Provide the guinea pig with a cage full of a few inches of bedding made of ripped paper strips, you will also need to supply it with a water bottle and a food dish.",
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"Provide the guinea pig with a cage full of a few inches of bedding made of ripped jeans material, you will also need to supply it with a water bottle and a food dish."
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],
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"target": "A",
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"id": 0,
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"group_id": 0,
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"metadata": {}
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}
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```
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*Note: Some content was truncated for display.*
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## Prompt Template
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**Prompt Template:**
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```text
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Answer the following multiple choice question. The entire content of your response should be of the following format: 'ANSWER: [LETTER]' (without quotes) where [LETTER] is one of {letters}.
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{question}
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{choices}
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```
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## Usage
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### Using CLI
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```bash
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evalscope eval \
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--model YOUR_MODEL \
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--api-url OPENAI_API_COMPAT_URL \
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--api-key EMPTY_TOKEN \
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--datasets piqa \
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--limit 10 # Remove this line for formal evaluation
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```
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### Using Python
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```python
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from evalscope import run_task
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from evalscope.config import TaskConfig
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task_cfg = TaskConfig(
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model='YOUR_MODEL',
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api_url='OPENAI_API_COMPAT_URL',
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api_key='EMPTY_TOKEN',
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datasets=['piqa'],
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limit=10, # Remove this line for formal evaluation
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)
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run_task(task_cfg=task_cfg)
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```
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